1. Technical Field
The present invention relates to data processing systems and, more particularly, to techniques for searching text strings for matches against a database of keywords to facilitate a search and retrieval mechanism.
2. Description of the Related Art
It is known in the art to provide computer-assisted diagnostic tools to assist end users in identifying and solving computer problems. Adaptive Learning (ADL) is one such diagnostic tool that provides a natural language interface for searching a database comprising active solutions to particular user problems. ADL has been implemented in known commercial products, such as the Tivoli Service Desk Version 5.0 Expert Advisor. ADL accepts unstructured textual descriptions and searches the descriptions for user-defined keywords. Each keyword is associated with a concept, and several keywords may be associated with a single concept. Thus, for example, the keywords crash, lock and freeze may have the single concept crash representing them. ADL uses the keywords and concepts to search a knowledge base for solutions related to a user's problem description. The solutions are then listed with a score indicating their relationship to a current problem.
In earlier ADL versions, these natural language descriptions were broken down into discrete words based on space delimitation. Each word was then compared for matches to a list of user-defined keywords. This ADL algorithm was not sufficient for use in an International application for several reasons. First, because many non-English languages do not use space delimitation in their writing systems, it was not possible to break down the natural language description into discrete words. Moreover, the techniques used in such prior versions for matching text against user-defined keywords did not operate against a full range of non-English characters.
There remains a need to provide new and improved adaptive learning methods and systems that address these and other deficiencies of the prior art.